The future of data architecture is being written. Come help shape it.

Transactional workloads demand low-latency, row-level writes. Analytical workloads demand high-throughput columnar scans across billions of rows. We’re coming together for a single day for real talk about how teams are solving this tension, whether through converged systems, purpose-built stacks, or something in between, is one of the most important architectural questions in the industry right now.

We’re looking for these themes: 

What you tried — war stories from running both workloads on one system, or from building a multi-system stack. What broke, what it cost, what you'd do differently.

What your architecture looks like today — case studies from data teams who have built and operated data systems at scale. Real systems, real tradeoffs, real numbers.

How to navigate the decision — the migration path, the operational reality, the organizational change. How teams are making these calls and living with the consequences.

What we don't want: Product pitches. One-sided benchmarks. "It depends" talks with no concrete conclusions. 

Who should apply: Engineers and architects who have built or broken data systems at scale. Whether you believe in convergence, best-of-breed, or something else entirely, if you have real experience and honest observations, we want to hear from you. The audience will have plenty of opinions.

We will cover expenses only if required